An Adaptive Charging Strategy of Lithium-ion Battery for Loss Reduction with Thermal Effect Consideration

Yujie Ding, Haimeng Wu, Zhiwei Gao, Hailong Zhang
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引用次数: 2

Abstract

With the increasing deployment of the electric vehicles, the study of advanced battery charging strategy has become of great significance to improve charging performance with reduced loss. This paper presents an optimized adaptive charging strategy for EV battery packs based on a developed system loss model. An electrical model integrated with thermal properties for the lithium-ion battery with cooling as well as a full loss model for the power converter have been included in this complete model. To reduce the overall loss of the charging system, the influence of temperature and varying internal resistance at different state of charge (SOC) have been considered to obtain an objective function. Moreover, an enhanced particle swarm optimization (PSO) algorithm is proposed and applied to speed up convergence time as well as enhance the precision of the solution. The results show that this proposed strategy can reduce the total loss by 4.01% and a 7.48% decrease of the charging time compared with the classical approach without applying this optimization.
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考虑热效应的锂离子电池自适应充电策略
随着电动汽车的日益普及,研究先进的电池充电策略对提高充电性能、降低损耗具有重要意义。提出了一种基于系统损耗模型的电动汽车电池组优化自适应充电策略。在这个完整的模型中包括了一个与冷却锂离子电池的热特性集成的电气模型,以及一个电源转换器的全损耗模型。为了降低充电系统的总损耗,考虑了温度和不同荷电状态下内阻变化的影响,得到了一个目标函数。在此基础上,提出了一种改进的粒子群优化算法(PSO),提高了求解的精度和收敛速度。结果表明,与未进行优化的传统方法相比,该策略可使总损耗降低4.01%,充电时间减少7.48%。
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